Boosting Software Development Using Machine Learning (Artificial Intelligence-enhanced Software and Systems Engineering)

個数:

Boosting Software Development Using Machine Learning (Artificial Intelligence-enhanced Software and Systems Engineering)

  • 在庫がございません。海外の書籍取次会社を通じて出版社等からお取り寄せいたします。
    通常6~9週間ほどで発送の見込みですが、商品によってはさらに時間がかかることもございます。
    重要ご説明事項
    1. 納期遅延や、ご入手不能となる場合がございます。
    2. 複数冊ご注文の場合は、ご注文数量が揃ってからまとめて発送いたします。
    3. 美品のご指定は承りかねます。

    ●3Dセキュア導入とクレジットカードによるお支払いについて
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Hardcover:ハードカバー版/ページ数 320 p.
  • 商品コード 9783031881879

Full Description

This book explores the transformative effects of AI and ML on software engineering. It emphasizes the potential of cutting-edge software development technologies such as Generative AI and ML applications. This book incorporates data-driven strategies across the entire software development life cycle, from requirements elicitation and design to coding, testing, and deployment. It illustrates the evolution from traditional frameworks to agile and DevOps methodologies. The potential of Generative AI for automating repetitive tasks and enhancing code quality is highlighted, along with ML applications in optimizing testing, effort estimation, design pattern recognition, fault prediction, debugging, and security through anomaly detection. These techniques have significantly improved software development efficiency, predictability, and project management effectiveness. While remarkable progress has been made, much remains to be done in this evolving area. This edited book is a timely effort toward advancing the field and promoting interdisciplinary collaboration in addressing ethical, security, and technical challenges.

Contents

1.Transforming Software Development: From Traditional Methods to Generative Artificial Intelligence.- 2.Case Study: Transforming Operational and Organizational Efficiency Using Artificial Intelligence and Machine Learning.- 3.Revolutionizing Software Development: The Transformative Influence of Machine Learning Integrated SDLC Model.- 4.Generative Coding: Unlocking Ontological AI.- 5.Case Studies: Machine Learning Approaches for Software Development Effort Estimation.- 6.Hybridizing Metaheuristics and Analogy-based Methods with Ensemble Learning for Improved Software Cost Estimation.- 7.A Review on Detection of Design Pattern in Source Code Using Machine Learning Techniques.- 8.Machine Learning Techniques for the Measurement of Software Attributes.- 9.An Effective Analysis of New Metaheuristic Algorithms and its Performance Comparison.- 10.Empowering Software Security: Leveraging Machine Learning for Anomaly Detection and Threat Prevention.- 11.Sentiment Analysis on Movie Reviews Using the Convolutional LSTM (Co-LSTM) Model.- 12.An Overview of AI Workload Optimization Techniques.- 13.Opportunity Discovery for Effective Innovation Using Artificial Intelligence.- 14.Applications of Machine Learning Algorithms in Open Innovation.

最近チェックした商品